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Chemicals Detection in Water by SENSIPLUS Platform: Current State and Ongoing Progress

  • Carmine Bourelly
  • M. FerdinandiEmail author
  • M. Molinara
  • L. Ferrigno
  • Roberto Simmarano
Conference paper
  • 58 Downloads
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 629)

Abstract

The challenge to detect contaminants inside water solutions is addressed in this paper, through the use of an integrated, low-cost, smart and IoT platform, namely SENSIPLUS. In particular, the complete process from the sensing phase to classification and results analysis is provided with further investigations about the limitations of the current proposal and the description of a further processing technique that promises to improve classification accuracy. The classification is performed by adopting machine learning techniques, particularly Artificial Neural Network, that well fits the implementation on a low-cost microcontroller, as the one SENSIPLUS platform uses.

Keywords

Water quality Contaminant detection Machine-learning Sensors IoT 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Carmine Bourelly
    • 1
  • M. Ferdinandi
    • 2
    Email author
  • M. Molinara
    • 2
  • L. Ferrigno
    • 2
  • Roberto Simmarano
    • 1
  1. 1.Sensichips s.r.l.ApriliaItaly
  2. 2.Department of Electrical and Information EngineeringUniversità degli studi di Cassino e del Lazio MeridionaleCassinoItaly

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